Although human exposure to toxicants occurs as a complex mixture, risk assessments are typically based on[unreadable] single chemical studies conducted in rodent models. Limitations associated with current approaches are[unreadable] increasingly being questioned due to the potential for significant health, societal and economic[unreadable] consequences. In order to improve the quantitative risk assessment of chronic and subchronic exposure to[unreadable] synthetic and natural chemicals and their complex mixtures, uncertainties within the source-to-outcome[unreadable] continuum must be minimized in the context of the whole organisms, and its genome. In this proposal,[unreadable] 2,3,7,8-tetrachlrodibenzo-p-dioxin (TCDD), 3,3',4,4',5-pentachlorobiphenyl (PCB126), and 2,2',4,4',5,5'-[unreadable] hexachlorobiphenyl (PCB153) as well as a reconstituted mixture that reflects environmental levels of these[unreadable] contaminants will be systematically examined to elucidate the mechanisms of action of additive, antagonistic[unreadable] and synergistic interactions that occur at molecular and physiological levels. Ray designs and modeling[unreadable] approaches will be used to minimize full factorial studies in order to investigate the hypothesis that a mixture[unreadable] of TCDD, PCB126 and PCB153 at environmentally relevant levels elicit non-additive hepatotoxic effects.[unreadable] Dose- and time-dependent hepatic gene expression and fatty liver effects will be assessed using a mouse[unreadable] cDNA array enriched with dioxin responsive genes and complementary histopathology approaches.[unreadable] Microarray data will be computationally integrated with histopathology and clinical chemistry to identify[unreadable] associations between changes in gene expression and physiological/toxic outcomes that facilitates the[unreadable] elucidation the mechanisms of action of dioxin-mediated fatty liver toxicity. The mixture will then be[unreadable] examined to detect and characterize the additive, synergistic and antagonistic interactions that affect the[unreadable] fatty liver response using response surface models for genes associated with fatty liver. This proposal will[unreadable] not only develop innovative and credible statistical strategies to rigorously assess interactions induced by[unreadable] mixtures containing chemicals that use a common mechanism of action, but will also further elucidate[unreadable] mechanisms of toxicity associated with TCDD-induced fatty.